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Distance Based Model, 샘플 사이즈만큼 일부만 데이터를 학습하면 추가 학습에서 성능이 떨어지니 전체 데이터를…

- - - - group margin 0.01 :check:
      - mse margin 0.005 :check:
      - cos margin 0.003 :check:
    - - Sequential Sampling :check::
      - batch size 8 :check:
      - Random Sampling :pencil2:
    - - training 2023-10-01 ~ 2023-10-21 :check:
      - validation 2023-10-22 ~ 2023-10-26 :check:
      - test 2023-10-27 ~ 2023-10-31 :check:
    - - depart user epochs 5 :check:
      - user program epochs 10 :check:
      - group epochs 40 :check:
    - - sgd
        
        learning rate 0.01 :check:
    - - step lr
        
        step size 50 :check:
- - - - 랜덤 샘플링 :check:
      - batch size 8 :check:
      - sample size 1024, 2048 :check:
      - 전체 이벤트 비율 샘플링 :pencil2:
      - 사용자 이벤트 동일량 샘플링 :pencil2:
    - - 학습+검증1일/테스트1일 :pencil2:
      - 학습1일/검증1일/테스트1일 :pencil2:
    - - mse margin 0.005 :check:
      - group margin 0.01 :check:
      - cos margin 0.003 :check:
    - - depart user epochs 5 :check:
      - group epochs 40 :check:
      - user program epochs 10 :check:
    - - sgd
        
        learning rate 0.00001 :check:
        
        learning rate 0.000001 :check:
        
        learning rate 0.001 :red_cross:
        
        learning rate 0.01 :red_cross:
      - adam
        
        learning rate 0.01 :red_cross:
        
        learning rate 0.001 :check::
        
        learning rate 0.00001 :red_cross:
        
        learning rate 0.000001 :red_cross:
      - adamw
        
        learning rate 0.01 :red_cross:
        
        learning rate 0.001 :check:
        
        learning rate 0.00001 :red_cross:
        
        learning rate 0.000001 :red_cross::
    - - step lr
        
        step size 4 :red_cross:
        
        step size 5 :check:
        
        step size 2 :red_cross:
        
        step size 50 :red_cross:
      - exp lr
        
        gamma 0.5 :red_cross: